code: def full_loop(self, num_inference_steps=10, seed=0, **config):
      scheduler_class = self.scheduler_classes[0]
      scheduler_config = self.get_scheduler_config(**config)
      scheduler = scheduler_class(**scheduler_config)
  
      model = self.dummy_model()
      sample = self.dummy_sample_deter
      generator = torch.manual_seed(seed)
  
      scheduler.set_timesteps(num_inference_steps)
  
      for t in scheduler.timesteps:
          residual = model(sample, t)
          sample = scheduler.step(
              residual, t, sample, generator
          ).prev_sample
  
      return sample
  
imports: import tempfile
  from typing import Dict, List, Tuple
  import torch
  from diffusers import LCMScheduler
  from diffusers.utils.testing_utils import torch_device
  from .test_schedulers import SchedulerCommonTest
label_desc: Use image node_id 15 for calling the LCMSchedulerTest obj's underlying member method code with example usage: obj.full_loop(num_inference_steps, seed) and returns: sample